Research Teams in Group
Biomedicine and signal processing
Bioinformatics

Leader: prof. Ing. Ivo Provazník, Ph.D.
Group website: https://www.ubmi.fekt.vut.cz/skupina-mapovani-farmakoforu-virtualni-screening
We develop new methods for the numerical processing of large-scale genomic data, emphasizing de novo genome assembly, genotyping of novel bacterial strains, and metataxonomic and metagenomic studies. The group also investigates and structures new medicals via in silico modeling of molecular interactions and by using virtual screening instruments.
Major 4-year outputs:
- Software tools for the numerical processing of large-scale genomic data.
- Software tools to align differently long genomic signals (implementation in Oxford Nanopore sequencers).
- Software tools for the lossless decimation of large-scale genomic signals.
- Software tools to process and analyze genomic, transcriptomic, and epigenetic data.
- Software tools to digitize and process images obtained through the gel electrophoresis of DNA molecules.
Brain Diseases Analysis Laboratory (BDALab)

Leader: Jiří Mekyska, Ph.D.
Group website: http://bdalab.utko.feec.vutbr.cz/
The researchers explore paraclinical diagnosis and monitor neurodegenerative diseases (Parkinson’s and Alzheimer’s diseases, dementia with Lewy bodies) by utilizing acoustic voice or speech analysis together with online handwriting, movement, and sleep analyses. Such methods, exploiting the eHealth, mHealth, and Health 4.0 approaches, are regularly employed by neurologists to examine the pathophysiological mechanisms and to investigate the treatment perspectives.
The group collaborate with eminent psychologists from the Academy of Sciences of the Czech Republic and the University of Haifa to devise novel, objective methods for diagnosing and evaluating developmental dysgraphia.
Major 4-year outputs:
- Matematical models to predict, with a two-year horizon, cognitive deficit in patients suffering from Parkinson’s disease. Similarly, machine learning was used to allow the automated evaluation or diagnosing of gait abnormalities and Parkinsonic dysgraphia; we also created a remote system to monitor a patient’s sleep by utilizing a smart wristband.
- A tool facilitating the acoustic analysis of speech/voice disturbances, which finds application in the tracing and assessment of the effect brought by new treatment methods.
- A system for the automated evaluation of developmental dysgraphia, exploiting machine learning and online handwriting analysis.
- A system to diagnose and evaluate Parkinsonic dysarthria.
- A system enabling quantitative speech or voice analysis in patients with primary progressive aphasia.
Cell biology and tissue engineering

Leader: Vratislav Čmiel, Ph.D.
Group website: https://www.ubmi.fekt.vut.cz/skupina-experimentalnich-mikroskopickych-technik-pro-bunecne-inzenyrstvi
Within molecular biology, we specialize in developing and implementing new microscopic methods to investigate the electrical and structural properties of cells. Our experts perform multiple diverse experiments ranging from the measurement of cell metabolism and metabolic or substance toxicity to forming an artificial vein based on live cells.
Major 4-year outputs:
- A miniature optical detector of albumin for smartphones.
- Patent: An infrared spectroscopy system.
- A methodology for volume imaging and multimodal volume data analyses in cell engineering, supported by advanced image processing algorithms and a scientific confocal microscope allowing spectral measurement.
- A methodology for designing and executing experiments in cell and tissue electrophysiology, using patch clamping devices and microelectrode fields combined with opthogenetic manipulation including visualization, analysis, and statistical data processing.
Biomedical signal processing

Leader: Assoc. Prof. Jana Kolářová
Group website: https://www.ubmi.fekt.vut.cz/skupina-zpracovani-analyzy-zaznamu-ekg
We create smart technologies to facilitate the monitoring and earlier diagnosis of patients in cardiology, neurology, and other branches of clinical medicine. Our aim is to connect the knowledge acquired through experimental research and clinical practice with recent findings in biological signal processing, smart sensors, and artificial intelligence to form fuctional clusters yielding faster and more effective medical care.
Major 4-year outputs:
- Software tools for quality estimation and adaptive filtering in biomedical signals.
- Software tools to enable, by utilizing machine learning methods, automated classification of atrial fibrillation and other cardiac rhythm disorders.
- Software tools allowing automated measurement and analysis of clinical and experimental ECG signals.
- Patent: A device for the optical sensing of electrical activity in a live tissue.
Medical image processing

Leader: Assoc. Prof. Radim Kolář
Group website: https://www.ubmi.fekt.vut.cz/skupina-zpracovani-obrazu-v-mikroskopii
Within medical image processing, we concentrate on the following tasks and domains: the development and application of software instruments used for the CT, PET, and MRI imaging modalities; monitoring and classification of objects in a videosequence; diagnosing retinal diseases; and monitoring of vital functions with various types of video camera. Our aim is to develop techniques leading towards easier and more effective use of information technologies within the identification and diagnosis of diverse diseases.
Major 4-year outputs:
- Patent: An opthalmological, retina and iris sensing device with an expert eye diagnosis system.
- Utility model: A device for the sensing and recognition of the iris and retina.
- Software tools to support glaucoma diagnosis via advanced analysis of retina images.
- Software tools for merging 2D image data obtained from a fundus camera.
- Software tools measuring bone density in spinal CT images.
- Software tools to identify pathological changes in the human spine.
- Software tools for automated analysis of CT images of the brain.
- Software tools to perform automated analysis of image data acquired via 3D subtraction angiography of the lower extremities.
Nanogroup: LabSensNano

Leader: Assoc. Prof. Jaromír Hubálek
Group website: http://www.umel.feec.vutbr.cz/labsensnano/
The laboratory experts examine the applicability of nanotechnologies in both general sensorics and the development of sensors of various quantities. The corresponding work involves the designing of not only microsensors to detect gases via nanoparticles but also nanostructured and functionalized electrodes to be employed in electrochemical sensors and biosensors. Other investigated subjects prominently include advanced techniques for the diagnostics and subsequent analysis of substances that find use in medicine.
Major 4-year outputs:
- A technique to allow the processing of a signal from a bolometer (bolometer array) and an electronic system to perform the task: the relevant patent has been put into practice abroad.
- A miniature bolometer membrane with increased absorption and a procedure to form a bolometer absorption layer: the relevant patent has been put into practice abroad.
- A 100-pixel MEMS with bolometers.
Advanced Signal Processing

Leader: Prof. Zdeněk Smékal
Group website: http://www.splab.cz/
The researchers design and implement patient monitoring systems within the Health 4.0 concept. Further activities include analyzing speech signals and online handwriting; event recognition in audio and video signals; audio signal reconstruction; and compressive sensing, analysis, and modeling in acoustics and electroacoustics.
Major 4-year outputs:
- An advanced camera surveillance security system applicable in infrastructures or public spaces and developed in collaboration with the company JIMI CZ a.s. The product comprises software facilitating the identification of persons, monitoring and evaluating their movement, detecting unattended baggage or fire, and performing other relevant functions.
- A system that automatically determines whether a signal recorded by a UWB receiver has been distorted due to, for example, reflection from or passage through an obstacle; the actual development resulted from joint efforts of the group and the company Sewio Networks s.r.o. The technology enables us to localize more accurately the position of a receiver in a closed space.
- A system for radio broadcast monitoring and remote surveillance, capable of evaluating the audio signal quality and technical problems in broadcasting; using the system’s potential, up to 16 radio stations can be remotely surveyed from a single location. The entire solution was custom-developed for the German company D.F.M.
- Multiple clients, such as Honeywell, submitted orders for the identification and analysis of noise or its sources in machines and instruments, including noises with acoustic pressure levels close to the threshold of hearing; to satisfy this type of demands, the group operates an anechoic chamber. For the companies Schneider Electric, DISK Multimedia, and FLEA Microphones, among others, the properties of LF audio and electroacoustic devices were analyzed.
Data-Mining research group

Leader: Assoc. Prof. Radim Burget
Group website: https://www.six.feec.vutbr.cz/research-groups/signal-processing/
The experts investigate algorithms and methods enabling the analysis and processing of unstructured data; other main activities include examining big-data and parallel algorithms to design comprehensive artificial intelligence systems.
Major 4-year outputs:
- A scalable big-data solution developed in collaboration with the Honeywell company to continuously analyze several tens of terabytes of data in a computing cloud. The information from 1.5 million sensors allows the instrument to recognize possible cost savings, at a yearly amount of $6.8 mil.
- Joint research with the Webnode company yielded a software solution exploiting artificial intelligence. The product is capable of analyzing messages or reports received by Webnode‘s customer service center to select, prioritize, and reduce the response time in the most significant items.
- A cooperation program involving Honeywell resulted in a specialized, artificial intelligence-based tool tailored to suit a pilot’s flight plan. The central functions consist in analyzing and intepreting thousands of NOTAM messages, which, after being evaluated, are merged with the pilot’s maps to increase the safety of the flight; in this context, the research brought interesting implications for air navigation in general.

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